class_docstr: Class for complement graphs.
  
  The main goal is to be able to work with big and dense graphs with
  a low memory footprint.
  
  In this class you add the edges that *do not exist* in the dense graph,
  the report methods of the class return the neighbors, the edges and
  the degree as if it was the dense graph. Thus it's possible to use
  an instance of this class with some of NetworkX functions.
docstr: Return an iterator over all neighbors of node n in the
  dense graph.
docstr_tok: ["Return","an","iterator","over","all","neighbors","of","node","n","in","the","dense","graph","."]
code: def neighbors(self, n):
      """Return an iterator over all neighbors of node n in the
      dense graph.
  
      """
      try:
          return iter(set(self.adj) - set(self.adj[n]) - {n})
      except KeyError as err:
          raise nx.NetworkXError(
              f"The node {n} is not in the graph."
          ) from err
  
file_path: networkx/examples/subclass/plot_antigraph.py
imports: import matplotlib.pyplot
  import networkx
  from networkx import Graph
label_desc: Use image node_id 3 for calling the AntiGraph obj's underlying member method code with example usage: obj.neighbors(n) and returns: iter